Organisms devote a significant fraction of their genomes to encoding regulatory information which specifies when and where different genes should be turned on or off. Such information is essential for understanding development, tissue specificity, and cellular response to the environment and has great importance for understanding the molecular basis of disease. The one dimensional regulatory programs encoded in DNA are executed by transcription factors which respond to different conditions and regulate gene expression combinatorially, leading to complex regulatory networks. The goal of the proposed research is to develop theoretical models and computational algorithms to decipher the regulatory programs and to reconstruct the transcription networks in the model organism Saccharomyces cerevisiae. The following are the specific aims: 1) to systematically map the DNA recognition sites and target genes of transcription factors in the genome, 2) to identify environmental and genetic perturbations under which each transcription factor is activated or deactivated, 3) to systematically analyze combinatorial regulation by multiple transcription factors, 4) collaborate with two experimental labs to address specific problems of transcriptional regulation and combinatorial control, and 5) to build databases and online tools for the biological community to analyze gene expression data and transcriptional regulation. We will develop methods integrating information from the genome sequences for several yeast species and genome-wide functional data, and we will combine bioinformatics analysis with mechanistic models of gene regulation.